again congratulations for all your efforts in putting order in all these factorizations. We have a contribution and I would ask if it could be added to your list. It is called BALM and it is on this month PAMI issue:

Abstract—This paper presents a uniﬁed approach to solve different bilinear factorization problems in computer vision in the presence of missing data in the measurements. The problem is formulated as a constrained optimization where one of the factors must lie on a speciﬁc manifold. To achieve this, we introduce an equivalent reformulation of the bilinear factorization problem that decouples the core bilinear aspect from the manifold speciﬁcity. We then tackle the resulting constrained optimization problem via Augmented Lagrange Multipliers. The strength and the novelty of our approach is that this framework can handle seamlessly different computer vision problems. The algorithm is such that only a projector onto the manifold constraint is needed. We present experiments and results for some popular factorization problems in computer vision such as rigid, non-rigid and articulated Structure from Motion; photometric stereo and 2D-3D non-rigid registration.